Predicting allergic contact dermatitis: A hierarchical structure-activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

Subhash C Basak, Denise Mills, Douglas M Hawkins

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13 Scopus citations

Abstract

A hierarchical classification study was carried out based on a set of 70 chemicals-35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

Original languageEnglish (US)
Pages (from-to)339-343
Number of pages5
JournalJournal of Computer-Aided Molecular Design
Volume22
Issue number6-7
DOIs
StatePublished - Jun 2008

Bibliographical note

Funding Information:
Acknowledgements This is contribution number 482 from the Center for Water and the Environment of the Natural Resources Research Institute. Research reported in this paper was supported in part by Grant F49620-02-1-0138 from the United States Air Force and Cooperative Agreement Number 572112 from the Agency for Toxic Substances and Disease Registry. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Office of Scientific Research, the U.S. Government, or the Agency for Toxic Substances and Disease Registry.

Keywords

  • Allergic contact dermatitis
  • Hierarchical structure-activity relationship
  • Model validation
  • Ridge linear discriminant analysis
  • Ridge regression
  • Theoretical molecular descriptors

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